Led venture with third party test equipment supplier to develop “Motorola” scripts on a base station emulator in which Motorola received royalty payments allowing vendor to sell scripts to other customers.

1985 - 1990

Section Manager

Led the growth of Automatic Vehicle Location business from 5 to 90 customers through a wide range of activities including product integration, customer technical and marketing interface, customer support, product marketing, manufacturing, and system stress test.

Education

Jan 1991 - May 1996

MBA - Engineering and Technical Management

University of Dallas

Aug 1972 - May 1976

BSEE

Summary

Director of Operations

Technical leader as Director of Operations with a Six Sigma Black Belt.Proven success in developing and sustaining business opportunities at lowest cost and managing projects throughout the lifecycle. Goal oriented with ability to solve complex problems and deliver projects within cost, schedule, and quality requirements achieving customer delight.

Accomplishments

Business Leader

Create business plan establishing and leading a service business performing CDMA Cellular Mobile Station – Base Station Interoperability test currently generating annual income of greater than $10M.

Led an organization consisting of software and hardware development engineers, field deployment engineers, manufacturing, and marketing in support of Motorola’s Automatic Vehicle Location product resulting in growth of business from 5 to 90 customers over 3 years.

Six Sigma Black Belt

Enlisting a cross functional team improving customer user documentation using DMAIC Six Sigma process resulting in a reduction of system outages and customer found defects, increasing customer satisfaction and yielding an annual savings of approximately $1M.

Reduce system test first execution cycle time from 12 to 6 weeks using Lean Six Sigma process resulting in an annual savings of over $750K.

Facilitated a DMAIC Six Sigma project with the System Test team in Beijing to introduce a feedback mechanism into system test reducing escaped defects by at least 20%.

Champion formation of team performing software reliability modeling and reliability simulation identifying end of system test phase resulting in reduction of escaped defects and improving customer satisfaction.

Conduct cross functional team as System Test (Functional, Regression, Performance, Stress, and Extended Life Test) release Project Manager, introduce process improvements, reducing defects escaping from system test by 67% and shipping the release on time.

Who’s Who Among Students in American Universities and Colleges, May 1996.

Objective

Seeking a management/director position in a small to mid sized company where I can use my vast engineering, process, quality, software reliability, software test and six sigma black belt experiences to increase shareholder value for a growing endeavor.

System Test

System testing of software or hardware is testing conducted on a complete, integrated system to evaluate the system's compliance with its specified requirements. System testing falls within the scope of black box testing, and as such, should require no knowledge of the inner design of the code or logic.
As a rule, system testing takes, as its input, all of the "integrated" software components that have successfully passed integration testing and also the software system itself integrated with any applicable hardware system(s). The purpose of integration testing is to detect any inconsistencies between the software units that are integrated together (called assemblages) or between any of the assemblages and the hardware. System testing is a more limiting type of testing; it seeks to detect defects both within the "inter-assemblages" and also within the system as a whole.
System Testing includes but is not limited to:
GUI software testing
Usability testing
Performance testing
Compatibility testing
Error handling testing
Load testing
Stress testing
User help testing
Security testing
Capacity testing
Sanity testing
Smoke testing
Exploratory testing
Ad hoc testing
Regression testing
Reliability testing
Recovery testing
Installation testing
Recovery testing and failover testing.
Accessibility testing

Customer Relations

Work with customers for the purpose of improving the quality of the product. Identify the deployment plans, concerns, requirements, soft-spots, and other customer factors. Make presentations to customers as to the test status of the product, escaped defect analysis, and other concerns of the customer.

Global Management

Management experience with teams in Japan, China, and Europe.

Visual Basic For Applications

Visual Basic for Applications (VBA) is an implementation of Microsoft's event-driven programming language Visual Basic, and associated integrated development environment (IDE), which is built into most Microsoft Office applications (Word, Excel, Power Point). By embedding the VBA IDE into their applications, developers can build custom solutions using Microsoft Visual Basic. It can be used to control almost all aspects of the host application, including manipulating user interface features, such as menus and toolbars, and working with custom user forms or dialog boxes.

Six Sigma Processes

Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and variability in manufacturing and business processes. It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization ("Black Belts","Green Belts", etc.) who are experts in these methods. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified financial targets (cost reduction or profit increase).
DMAIC
DMAIC is used to reduce variation and improve the quality of an existing process. The five phases in the DMAIC project methodology are:
Define high-level project goals and the current process.
Measure key aspects of the current process and collect relevant data.
Analyze the data to verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered.
Improve or optimize the process based upon data analysis using techniques like Design of experiments.
Control to ensure that any deviations from target are corrected before they result in defects. Set up pilot runs to establish process capability, move on to production, set up control mechanisms and continuously monitor the process.
DMADV
Use for developing new processes or to create radical change in existing process. DMADV is also known as DFSS, an abbreviation of "Design For Six Sigma" (DFSS). The five phases in the DMADV project methodology are:
Define design goals that are consistent with customer demands and the enterprise strategy.
Measure and identify CTQs (characteristics that are Critical To Quality), product capabilities, production process capability, and risks.
Analyze to develop and design alternatives, create a high-level design and evaluate design capability to select the best design.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Verify the design, set up pilot runs, implement the production process and hand it over to the process owners.
DMADDD
Use to drive quantum efficiency in existing operations. DMADDD is also known as Lean Six Sigma. The six phases of the DMADDD project methodology are:
Define high-level project goals and the current process.
Measure key aspects of the current process and collect relevant data.
Analyze the data to verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Digitize requires the automation of repeatable steps to institutionalize and continue to improve the time savings.
Draw Down focuses on the elimination of parallel efforts and the handover of the process changes to the process owners.

Escaped Defect Analysis

The study of defects that escape one phase of the development process to determine how to improve Prediction, Prevention, and Containment processes.

Software Reliability Modeling

The science of assessing a software product's reliability to estimate the number of latent defects when it is available to cusotmers. It can also estimate the software reliability expressed in terms of MTTF. Two classes of models are used. The development lifecycle model and the test model. In each classificaiton there are many models to choose from. In the lifecycle, a common model is the Rayleigh model. In the test cycle, a common class of models is the non-homogeneous Poisson Process models.

Software Reliability Engineering

The science of producing software that meets the specified probability of failure-free operation for a specified period of time in a specified environment. There are four phases to producing highly reliable software:
Assessing: Assessing provides a framework and architecture to insure that you can deliver a highly reliable/available product that delights the customer in terms of cost of ownership. In this phase you need to identify the VOICE OF THE CUSTOMER and help establish customer expectations
Planning: The planning phase focuses on risk identification and establishing plans for risk mitigation so that we can deliver a highly reliable/available product. In this phase, it is critical to establish an architecture that permits accurate, timely, and meaningful fault detection to allow quick remote analysis/diagnosis, correction, and recovery of a given issue.
Execution: The Execution phase focuses on mitigating risks to reliability through creating fault free design, and through the detection and elimination of faults that find their way into the product.
Monitor / Control: There are two objectives to Monitor / Control. The first objective is to monitor the program “real-time” during the product development lifecycle to create a feedback loop around the Reliability process. In this effort, you will measure and compare results to the plans created in the Planning phase. When those measures are out of control from the plan, it shall be necessary to provide recommendations for corrective action. The second objective is to collect data from field results to take immediate corrective action for the customer and to update models and model databases for use in future projects.

Orthogonal Defect Classification

A foundation for providing analysis and feedback of defect data targeting quality issues in software design and code in a procedural language environment.

RF, Digital, and Analog Hardware Design

RF Hardware Design: The design of electronic circuitry that operates at frequencies at or above 100KHz. This circuitry is typically used in transmitter and receiver systems. This also includes the layout of printed wiring boards (printed circuit boards)
Digital Hardware Design: The design of combinational and sequential logic circuits using Boolean functions, Karnaugh Maps, and truth tables.
Analog Circuit Design: The design of electronic circuitry not described above.

ISO17025

ISO/IEC 17025 is the main standard used by testing and calibration laboratories. Originally known as ISO/IEC Guide 25, ISO/IEC 17025 was initially issued by the International Organization for Standardization in 1999. There are many commonalities with the ISO 9000 standard, but ISO/IEC 17025 adds in the concept of competence to the equation. And it applies directly to those organizations that produce testing and calibration results.

Continuous Improvement

A management process whereby delivery (customer valued) processes are constantly evaluated and improved in the light of their efficiency, effectiveness and flexibility.

Project Management

Planning, organizing, and managing resources to bring about the successful completion of a specific project goals and objectives. The objective is to deliver to the customer (internal or external) the product they want, when they want it, and at a cost agreeable to both.

Training, Mentoring, Coaching

Direct the development of training courses used internally and by customers.
Mentor employees in the performance of their job.
Mentor Green Belt and Black Belt candidates working on Six Sigma projects.
Taught Business Statistics at Texas Christian University Neely School of Business

Quality Systems Management

Manage product development quality focusing on Cost, Schedule, Cycle Time, and Quality of the product delivery to the customer.
Monitor and Audit development and test organizations.

The purpose of this document is to introduce the reader to a condensed presentation on the topics of Reliability, Availability, Maintainability, and Redundancy. It will provide theory and definitions sufficient for a rudimentary understanding of the subject. The document will go on to present the three mathematical tools, MIL-217 Parts Count, Bellcore and FITS, used in the analysis of the failure rate of circuit boards.
The topics of Reliability, Availability, Maintainability, and Redundancy form a unique engineering discipline based on applied mathematics and probability theory. It is extremely difficult, if not impossible, to identify and exactly quantify all variables which contribute to the failure of even the simplest components. Therefore probabilistic models are applied to large samples to obtain average results.
The approach to the study of Reliability, Availability, and Maintainability of a complex system is to break the system down to a level of functional units. These units can then be further subdivided into more simple functional blocks that can eventually be described by schematic diagrams. Once at the block diagram level it is easy to apply the tools (MIL-217, Bellcore, or FITS analysis) to estimate the steady-state failure rate of each block. Then each block can be recombined to provide the reliability of the unit. Then using Redundancy models, the units can be combined to determine the Reliability or Availability of the total System.